Towards accurate and automatic emergency department workflow characterization using a real-time locating system

ABSTRACT

This paper presents how patient throughput within an Emergency Department (ED) can be accurately and automatically characterized using a combination of data derived from a real-time location system (RTLS) and other traditional hospital IT systems such as Electronic Medical Records (EMR) and Laboratory Information Systems. Such insights can be used by a hospital to identify bottlenecks or inefficiencies and develop strategies to optimize and monitor patient flows. A descriptive, retrospective study was conducted among 1149 patients. Five KPIs, including time from arrival to triageand total length of stay, were used to evaluate ED timestamps to characterize the flow of the patient. A description of the techniques used to combine the various data sources to perform the accurate measurements is provided. The paper also describes the measurements obtained and indicates how real-time locating systems can contribute towards improving the quality of the timestamps generated compared to only using data from traditional hospital IT systems. A principial finding is that there is a large gap between the length of stay using only EMR data and the one computed combining EMR and RTLS data. Finally, the paper provides guidelines on how to deploy such a system effectively.

KEYWORDS:

• Real-time locating systems
• emergency department
• patient flow characterization
• measuring operational performance
• length of stay

Disclosure statement

No potential conflict of interest was reported by the authors. .

Notes

1 By Hospital Information Systems we refer to systems such as Electronic Medical Records (EMR), Laboratory Information Systems (LIS), Radiology Information Systems (RIS), Emergency Services (EMS), Internet-of-Medical Things (IoMT), e.g., an Internet-connected CT scanner. In Table 1 and Table 3, it is described how these different HIS are used.

Additional information

Funding

This work was supported by the HORIZON EUROPE Framework Programme [grant number 780495] and by the Hessian Ministry of Higher Education, Research, Science and the Arts.

Notes on contributors

Michael von Wagner

Michael von Wagner, as Chief Medical Informatics Officer (CMIO) at the Executive Department for medical IT-systems and digitalization, Medical Department 1, Frankfurt University Hospital, Michael von Wagner, MD, has medical responsibility for development of the hospital information system and implementation of digital strategy together with the CIO. Beside that he works as senior physician in gastroenterology.

Alexander Queck

Alexander Queck, M.D. is attending physician in gastroenterology and emergency medicine. He works in the Department of Internal Medicine 1, University Hospital Frankfurt, Germany. He is board certified in internal medicine, gastroenterology and emergency medicine. His research interests include emergency medicine and hepatology with focus on portal hypertension.

Pim Beekers

Pim Beekers currently works as a researcher at the National Care Institute in the Netherlands. He earned his Master degree in Health Sciences at Maastricht University in 2019. From 2020 to 2021, he worked at Philips on process optimization of patient care pathways.

Ludo Tolhuizen

Ludo Tolhuizen has been with Philips Research since 1986. He obtained his PhD in mathematics from Eindhoven University in 1996. His current research interests include Data Science and its application in the healthcare domain.

Anne Synnatschke

Anne Synnatschke holds a German Argentine double degree in Business Management (M.A.) and works for Philips Health Systems as Product Manager being responsible for the PerformanceFlow IoT solution. As Solution Project Manager, she orchestrates the implementation of “first of kind” installations with strategic customers in Philips' focus markets.

Josee Boesing

Josee Boesing has been working for Philips for 10 years, (Quality Specialist, Order Manager, Service Advisor/Clinical Application Specialist). With a nursing degree and extensive experience in Emergency, Intensive care, and Endoscopy, she brings insights from a clinical perspective, with Lean and Change Management to round off her qualifications.

Supriyo Chatterjea

Supriyo Chatterjea has been with Philips Research since 2011. He obtained his PhD in computer science from the University of Twente in 2008. He leads a team that develops solutions that combine IoT, Data Science and AI technologies to optimize operational workflows in hospitals.